Comments (5)
Have you run the create index before? It's a bit weird. Can you try restarting the database to see whether the issue still exists?
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I have stopped the server, removed the data directory and set up a completely fresh cluster with:
./initdb -k -D ../data/ -E UTF8 --no-locale -U postgres -W
My postgresql.auto.conf:
# Do not edit this file manually!
# It will be overwritten by the ALTER SYSTEM command.
shared_preload_libraries = 'vectors.so'
search_path = '"$user", public, vectors'
The error persists.
from pgvecto.rs.
Can you try remove all the file under pgdata/pg_vectors
?
from pgvecto.rs.
As said before, I started with a empty, freshly initialized $PGDATA directory. However, I think I have found a way to reproduce it:
postgres=# CREATE TABLE items (
id int4 GENERATED ALWAYS AS IDENTITY,
embedding vector(5) NOT NULL
);
postgres=# insert into items (embedding) values ('[1,2,3,4,5]');
INSERT 0 1
postgres=# CREATE INDEX ON items USING vectors (embedding vector_cos_ops);
CREATE INDEX
No problems.
postgres=# drop table items;
DROP TABLE
postgres=# CREATE UNLOGGED TABLE items (
id int4 GENERATED ALWAYS AS IDENTITY,
embedding vector(5) NOT NULL
);
postgres=# insert into items (embedding) values ('[1,2,3,4,5]');
INSERT 0 1
postgres=# CREATE INDEX ON items USING vectors (embedding vector_cos_ops);
ERROR: pgvecto.rs: The index is already existing in the background worker.
It's the UNLOGGED.
Since UNLOGGED is a supported directive for CREATE TABLE since PostgreSQL v9.1 (https://www.postgresql.org/docs/9.1/sql-createtable.html) I'd say, this is a bug. Or is it documented behavior?
best regards
Ernst-Georg
from pgvecto.rs.
It's intended behavior in 0.2.x
. It's solved in #414 and it will work in 0.3.0
.
from pgvecto.rs.
Related Issues (20)
- epic: Release 0.3.0 HOT 1
- benchmark: INT8 benchmark HOT 1
- test: 0.3 release test HOT 1
- chore: sync return when index creation
- Need a docker compose example HOT 4
- epic: Support SDKs in different programming languages HOT 4
- bug(cnpg): type "vector" does not exist HOT 1
- The default max_stack_depth parameter in the container image may be too small HOT 12
- How could I use AzureOpenAI to build LlamaIndex? HOT 2
- vector type not found in the database - pgvecto_rs.psycopg register_vector HOT 5
- copy with BINARY FORMAT fails with cannot find a dumper for type vector HOT 3
- sdk: Sparse vector indices type mismatch between sdk and function signature with numpy.ndarray
- How to find index size ? HOT 3
- Execute pg_resetwal in docker Unraid HOT 3
- feat: Support vector aggregation function HOT 1
- feat(fdw): How to be compatible with new pgvector types HOT 1
- feat: ANN benchmark HOT 3
- bench(fdw): Latency HOT 4
- fix(bench): Fix ZillizBench HOT 1
- feat: Add pgvecto.rs to vector hub HOT 2
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